The prevalence and moderating factors of sleep disturbances in people living with HIV: a systematic review and meta-analysis

This systematic review and meta-analysis aimed to investigate the prevalence of self-reported sleep disturbances in people living with HIV considering the effects of age, depression, anxiety, CD4 cell counts, time since HIV diagnosis, study region, and the instruments used to measure sleep disturbances. We searched PubMed, PsycINFO, and EMBASE to include eligible articles. In this meta-analysis of 43 studies, the pooled prevalence of self-reported sleep disturbances was 52.29% (95% confidence interval 47.69–56.87). The subgroup analyses revealed that variations in the sleep measurements and study region significantly contributed to the observed heterogeneity. In the meta-regression analyses, higher proportions of participants with depression or anxiety and longer times since HIV diagnosis were significantly associated with a higher prevalence of self-reported sleep disturbances after adjusting for mean age. Our findings emphasise the substantial burden of sleep disturbances in people living with HIV and identified comorbid depression and anxiety and the time since HIV diagnosis as significant moderators. These results underscore the importance of considering these factors when designing tailored screening programmes for high-risk patients and implementing early interventions to prevent and mitigate sleep disturbances in people living with HIV.


Study characteristics
The 43 studies were published between 1998 and 2023 and included a total of 28,480 participants with HIV infection.The sample sizes ranged from 25 to 13,700 participants.Of the 43 studies, 17 were conducted in North America (all in the United States), 11 were conducted in Asia (5 in China, 4 in Iran, 2 in Indonesia), 7 were conducted in Africa (4 in Ethiopia, 2 in Nigeria, 1 in the Republic of South Africa), 6 were conducted in Europe (2 in the United Kingdom, 2 in France, 1 in Greece, 1 in Romania), and 2 were conducted in South America (both in Brazil).Most of the studies were cross-sectional (k = 40).Thirty-four studies used the PSQI, one of which employed a 2-item PSQI.Nearly all the studies that used the full-item PSQI used a cut-off value of 5 to distinguish poor sleepers from good sleepers; one study instead used a cut-off value of 10 19 .Eighteen studies reported the percentage of comorbid depression, and 11 studies reported the percentage of comorbid anxiety.Twenty-eight studies reported the time since HIV diagnosis.Detailed information for each study is presented

Assessment of sleep disturbances among PLWH by moderators
Due to the high levels of heterogeneity, further subgroup analyses were performed to examine the prevalence of self-reported sleep disturbances based on the different measurements used in the studies.As shown in Fig. 3, the PSQI was the most frequently used measurement tool.The prevalence was significantly higher in studies using the PSQI (57.81%, 95% CI 52.63-62.90)compared with those using the ISI (28.46%, 95% CI 22. 59-34.72)or other sleep instruments (36.31%, 95% CI 21. 42-52.68).
When comparing studies published before 2015 with those published from 2015 onward, the group including papers published before 2015 (66.54%, 95% CI 57.09-75.38)showed a significantly higher prevalence of sleep disturbances compared to the group including papers published from 2015 onward (45.96%, 95% CI 41.13-50.83,p = 0.0002).When analysing 34 papers measured with PSQI, those published after 2015 demonstrated a significantly higher prevalence of sleep disturbances as well.
Additional meta-regression analyses were conducted to investigate the substantial heterogeneity across the studies.In the univariable meta-regression analyses, a higher proportion of participants with comorbid anxiety (β = 0.008, 95% CI 0.004-0.012,k = 11, Q M = 17.44, p < 0.001, Supplementary Fig. S5) was significantly associated with a higher prevalence of self-reported sleep disturbances.The mean age, proportion of participants with comorbid depression, mean CD4 cell counts, and mean time since HIV diagnosis were not significantly associated with the prevalence of sleep disturbances.After controlling for mean age, a higher proportion of participants with depression (β = 0.007, 95% CI 0.002-0.012,k = 17, Q M = 7.47, p = 0.024), longer time since HIV diagnosis (β = 0.023, 95% CI 0.002-0.043,k = 21, Q M = 6.41, p = 0.041), and higher proportion of participants with anxiety (β = 0.009, 95% CI 0.003-0.015,k = 9, Q M = 9.10, p = 0.011) were significantly associated with a higher prevalence of self-reported sleep disturbances.The mean CD4 cell count was not significantly associated with the prevalence of sleep disturbances, even after adjusting for age.Detailed results are reported in Table 2.

Publication bias
The funnel plot (Supplementary Fig. S1) and Egger's test (t = 4.03, p < 0.001) indicated significant publication bias.The results of the trim-and-fill analysis show that at least 16 additional studies would be required for a symmetrical effect size distribution (Supplementary Fig. S2).After incorporating these effects, the pooled estimate of the prevalence of self-reported sleep disturbances was 38.88% (95% CI 34.24-43.61),which is significantly lower than the prevalence based on the primary result (52.29% [95% CI 47.69-56.87]).These results suggest that studies reporting a lower prevalence of self-reported sleep disturbances were less likely to be published compared with those reporting higher prevalence rates.

Discussion
We performed this systematic review and meta-analysis to examine the prevalence of self-reported sleep disturbances in PLWH, building upon and extending the findings of a meta-analysis published in 2015 9 .We included 43 studies with a total of 28,480 participants.In our review, the pooled prevalence of sleep disturbances was 52.29% (95% CI 47.69-56.87),which is comparable to the prevalence of 58.0% reported in the previous meta-analysis 9 .These estimates are substantially higher than the reported estimate of 30% for the general population 22 .In the sensitivity analysis, the pooled prevalence remained robust at 51.17% (95% CI 46.15-56.18)after excluding two studies that potentially contributed to heterogeneity from the Baujat plot.The subgroup and meta-regression analyses revealed that the continent, comorbid depression rate, comorbid anxiety rate, time since HIV diagnosis, and instrument used to measure sleep disturbances were significant moderators.These findings enhance our understanding of the variability in the prevalence of sleep disturbances across the studies included in the meta-analysis.
The heterogeneity in the prevalence of sleep disturbances among PLWH can be attributed to the varying sleep measurement instruments in the included studies.In our review, the PSQI was the most frequently used measurement tool in studies collecting prevalence data, followed by the ISI.Consistent with previous meta-analyses of different populations [23][24][25] , we observed significant differences in the prevalence of sleep disturbances among PLWH in studies using different assessment instruments.The prevalence was significantly higher in the studies using the PSQI (57.80%, 95% CI 52.63-62.90)than in those using the ISI (28.46%, 95% CI 22.59-34.72)or other sleep instruments (36.31%, 95% CI 21. 42-52.68).This discrepancy may be attributed to variations in the range of symptoms covered by each instrument.For example, the ISI evaluates all three major insomnia symptoms-difficulty initiating sleep, difficulty maintaining sleep, and early morning awakening 26 -whereas the PSQI assesses a broad range of sleep domains influencing overall sleep quality.Considering that the previous meta-analysis (although it focused on individuals other than HIV-infected patients) found no significant difference in sleep disturbance prevalence between the PSQI and ISI subgroups, which had comparable numbers of studies 27 , the observed discrepancy in prevalence between the PSQI and ISI subgroups in our study may be attributed to an uneven distribution of studies within the subgroups, which had 34 and 5 studies, respectively.In addition, the study by Robbins et al. 20 reported a 100% prevalence of sleep disturbances in PLWH, which led to an overall higher prevalence rate in the studies using the PSQI.After excluding the study by Robbins et al., the prevalence of sleep disturbances decreased to 55.9% in the subgroup analysis.
Our findings show significant differences in the prevalence of sleep disturbances among the studied continents, with the highest prevalence observed in South America, followed by North America, Africa, Asia, and Europe.Given that the highest prevalence of depression in HIV-infected patients was reported in South America www.nature.com/scientificreports/and the lowest was reported in Europe 28 , psychological burden may have influenced the prevalence of sleep disturbances.In addition, a previous epidemiologic study in the general population reported that women are more likely to report sleep disturbances than men 22 ; thus, the relatively lower prevalence of sleep disturbances in Asia and Europe may have been influenced by the higher proportions of male participants in all the studies conducted in these regions.However, considering the sex disparities in the prevalence of HIV infection among continents, and noting that most of the studies included in this meta-analysis were conducted in North America with relatively fewer studies from Asia and Europe, further research regarding the impact of sex on sleep disturbances is www.nature.com/scientificreports/needed.We also found that of the many studies conducted in South and North America, all but two 29,30 used the PSQI to measure sleep disturbances.In light of our finding that the use of the PSQI was associated with a higher reported prevalence of sleep disturbances compared with other sleep instruments, methodological differences may have partially contributed to the geographical disparity in sleep disturbance rates.We observed that the prevalence of sleep disturbances was significantly lower in studies published from 2015 onward compared to those published before 2015.Regarding integrase inhibitor-based ART has fewer reported sleep-related side effects 31 compared to efavirenz 32 , which is known to increase sleep disturbances, this www.nature.com/scientificreports/finding may reflect the increased use of integrase inhibitors-based ART instead of efavirenz.In addition, considering previous findings suggesting an association between stigma and sleep impairment 33 , it is plausible that the decreasing HIV-related stigma over time 34 may have influenced the lower prevalence of sleep disturbance observed from 2015 onward.We found that higher proportions of patients with anxiety or depressive symptoms were associated with higher estimates of sleep disturbance prevalence even after adjusting for mean age.Given the bidirectional relationship between insomnia and depression and anxiety-where sleep disturbances can either precede or be caused by depression and anxiety 16 -our findings suggest that effective treatment of either sleep disturbances or depression/anxiety may potentially resolve or prevent the other, thereby improving quality of life.Given concerns about stigma, PLWH may hesitate to report psychological symptoms; thus, interventions and treatment for the relatively easy-to-report symptom of sleep disturbances may be more feasible than those for depression or anxiety.
We further found that a longer time since HIV diagnosis was associated with a statistically significant increase in the prevalence of sleep disturbances after adjusting for mean age.In recent years, advancements in ART and optimised virus control have led to a reduction in sleep disturbances previously associated with immunosuppression, opportunistic infection, and ART side effects, as observed in the 1990s 35,36 .However, the significant increase in sleep disturbances along the duration of HIV infection, despite good virus control and reduced ART side effects, suggests a potential influence of social and psychological factors.A lack of social support 14 or low socioeconomic status 36 may contribute to the sustained impact of sleep disturbances.Additionally, the internalised stigma PLWH experience due to their HIV status may be associated with depression and anxiety 37,38 .However, from the 20 studies that reported on the time since HIV diagnosis, the overall proportion of patients who were diagnosed with HIV over 5 years before was greater than 50%.Considering that previous studies have observed higher rates of sleep disturbances in the months soon after HIV diagnosis 5,39,40 , our findings should be interpreted with caution.
We also explored the impact of mean CD4 cell counts on the prevalence of sleep disturbances but found no significant association in our results.Previous findings have shown that lower HIV RNA levels were associated with higher sleep efficiency and revealed no relationship between lower CD4 cell counts and greater sleep disturbances 41 , which, together with our findings, suggests that HIV viral control may have a more significant impact on sleep disturbances than the CD4 cell count.However, given the scarcity of studies reporting HIV RNA levels in our review, we could not assess its relationship with the prevalence of sleep disturbances.Additional future analyses on this issue are necessary.
Furthermore, sleep disturbances include a wide range of disorders including insomnia, sleep-disordered breathing, hypersomnolence, circadian rhythm sleep-wake disorders, sleep-related movement disorders and parasomnias 42 .There are reports of higher prevalence of REM sleep behavior disorder and nocturia among PLWH 43 , as well as increased prevalence of obstructive sleep apnea 44 , indicating that sleep disturbances in this population extend beyond insomnia.Several pathophysiological changes suggest that HIV infection can cause sleep-wake dysregulation through early-stage immunological changes and sleep-promoting cytokines, while chronic immune activation and antiretroviral therapy side effects further disrupt sleep homeostasis 11 .Yet, the current review focused only on disturbances assessed via self-report measures, mainly evaluating insomnia.Therefore, additional research into the range of sleep disturbance disorders and their association with moderating factors is necessary.
In addition, social determinants of health, such as socioeconomic status (SES), are directly linked to the prevalence and incidence of sleep disturbances 45,46 .It has also been reported that socioeconomic determinants, including income, area of residence, and particularly educational attainment, are associated with HIV incidence 47 .Therefore, while our findings did not explicitly address various social determinants, it is also necessary to examine social determinants of sleep disturbances in PLWH.For instance, a study included in this meta-analysis also found that poor sleep quality in PLWH is significantly influenced by low monthly incomes and poor social support 48 .This suggests that addressing not only the depression, anxiety, and longer times since HIV diagnosis associated with sleep disturbances found in our study but also SES and other social determinants is beneficial for improving sleep health in PLWH.
The major strength of our study is that it is the most comprehensive systematic review to date on the prevalence of self-reported sleep disturbances in PLWH.More than half of the included studies were published in the last 5 years, allowing for a better reflection of recent trends.We also incorporated a detailed exploration of regional differences.Furthermore, we considered depression and anxiety as psychological moderators, which the www.nature.com/scientificreports/previous meta-analysis did not take into account.Our study also has several limitations.First, high heterogeneity was observed in the meta-analysis, as anticipated from psychiatric research using subjective self-reported measurements.Second, most included studies were cross-sectional, cohort, and case-control studies, raising the possibility of selection bias due to the absence of randomisation and complicating the validation of the direction of causality between sleep disturbances and moderators in PLWH.Third, the inclusion of only English studies and the omission of grey literature resulted in publication bias.Fourth, we did not incorporate prevalence data derived from objective measures of sleep, such as polysomnography and actigraphy.Fourth, it is difficult to generalise the differences in the prevalence of sleep disturbances between continents because the included studies were relatively localised rather than being conducted in diverse countries.Lastly, we did not account for the impact of ART, which could induce sleep disturbances.

Conclusion
This systematic review and meta-analysis demonstrated the pooled prevalence of self-reported sleep disturbances in PLWH, which was higher than that in the general population.Given the shift in focus from extending life expectancy to improving quality of life among PLWH, there is a need for effective evaluation and management of sleep disturbances in this population.Moreover, the study region, depression and anxiety comorbidity rates, time since HIV diagnosis, and sleep measurement tool used may be significant moderators of the prevalence of sleep disturbances in PLWH.These factors may therefore be useful in designing tailored screening programmes for high-risk patients and intervening early to prevent the onset and exacerbation of sleep disturbances in PLWH.

Design
The systematic review and meta-analysis were conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions 49 and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines 50 .The review protocol was prospectively registered in the PROSPERO database (registration number CRD42023468139).

Data source and search strategy
The search for eligible studies was conducted using three different databases-PubMed, PsycINFO, and EMBASE-from the inception of each database to May 16, 2023.We used the following search terms to search titles and abstracts: ("sleep*" OR "insomnia") AND ("HIV" OR "AIDS").Lists of the articles detected through the search were downloaded, stored, and reviewed using EndNote (version 21.2).

Study selection criteria
To be eligible for inclusion in the present meta-analysis, a study had to meet the following criteria: (1) participants were adult patients (≥ 18 years of age) with HIV infection (either tested or self-reported), (2) presented self-reported frequency data on sleep disturbances (including any type or diagnostic criteria) or relevant data that could be used to estimate the prevalence of sleep disturbances, (3) observational study design, including cross-sectional, cohort, case-control or longitudinal (with baseline data) studies, and (4) published in English.
Studies were excluded if they included only participants with sleep disturbance at the time of enrolment or if they reported only objective measures for sleep disturbances or single-item measures with binary response options.When duplicate data were found in multiple studies in the same database, only the study with the more comprehensive data was included for analysis.

Data extraction and quality assessment
Two independent investigators (SAL and JWO) conducted data extraction.Any discrepancies detected were resolved by consensus.The details collected included the first author, year of publication, study design, country in which the study was conducted, mean age of participants, percentage of male participants, number of HIVpositive participants, measure of sleep disturbances, measures of depressive and anxiety symptoms with relative cut-off scores, CD4 cell counts, mean time since HIV diagnosis in years, and prevalence of self-reported sleep disturbances.
For the current systematic review and meta-analysis, the quality of the included studies was evaluated using the Joanna Briggs Institute's critical appraisal tool, the Checklist for Prevalence Studies 51,52 .Two authors (SAL and JWO) again independently evaluated each of the included studies.Any discrepancies detected were resolved by reaching a consensus through discussion.The checklist consists of nine items with four possible answers-"yes", "no", "unclear", and "not applicable"-for assessing the appropriateness of the sample frame, sampling method, sample size, statistical analysis, response rate, and description of study subjects and settings as well as the sufficiency of the data analysis, validity of the methods, and reliability of the measurements.In this study, we calculated a quality score for each study by assigning 1 point to each item marked "yes" in the assessment and 0 points for all other responses.We summed the points for each study, and the possible scores ranged from 0 to 9. Based on this quality score, studies were classified into three groups: low quality (scores 0-2), moderate quality (scores 3-6), and high quality (scores 7-9).

Data analysis
All data analyses and visualisations were conducted with R (version 4.3.1)using the meta and metafor packages.Prevalence data were converted using a Freeman-Tukey double-arcsine transformation.The overall prevalence rates of self-reported sleep disturbances with corresponding 95% confidence intervals (CIs) were calculated with

Figure 1 .
Figure 1.PRISMA flow diagram of study selection.

Figure 2 .
Figure 2. Forest plot of pooled prevalence of self-reported sleep disturbances in people living with HIV.

Figure 4 .
Figure 4. Subgroup analysis by continent where the study was performed.

Table 1 .
Summary of the characteristics of the included studies.

Table 2 .
Association between sleep disturbances and moderators.† Each variable was adjusted for age.